Design, build, and maintain scalable data pipelines and systems using Python, PySpark, and AWS-native services.
Develop and optimize data platforms on AWS, leveraging technologies like Redshift, Glue, and Athena.
Mentor junior engineers and collaborate with cross-functional teams in an Agile environment.
Capital Technology Group provides expert consulting services in software development, digital transformation, and data analytics. Recognized as a Top Workplace by The Washington Post, they foster a culture where employees feel trusted and empowered.
Own the Airflow codebase end-to-end, building reusable templates and enforcing standards.
Build and extend large-scale Spark pipelines on AWS Glue and support migration to Databricks.
Drive data model improvements around commercial pharma data with focus on structure and lineage.
Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. As one of the fastest-growing SaaS companies in history, it surpassed $3B in revenue and values doing the right thing, customer success, employee success, and speed.
Design and build batch data pipelines that ingest, validate, and transform multi-billion-row datasets.
Model complex real-world data including dimensional models and temporal data.
Develop and operate workloads on lakehouse platforms like Databricks, Spark, and Delta.
Simulmedia builds an advanced TV and streaming advertising platform. They have a team of engineers, data scientists, and designers who are obsessed with building cutting-edge technology.
Lead, coach, and develop a global team of data engineers while guiding technical architecture and delivery.
Build and scale large-scale data pipelines, production datasets, and QA systems using Databricks, Airflow, SQL, and PySpark.
Partner with product and research teams to transform complex data into reliable, production-grade assets for customers and internal applications.
YipitData is a leading market research and analytics firm that analyzes billions of alternative data points to provide actionable insights for the disruptive economy. The company recently raised $475M, operates globally with offices in the US, APAC, and India, and has been recognized by Inc. as a Best Workplace for three consecutive years.
Design, build, and maintain scalable batch and streaming data pipelines.
Develop reliable ETL/ELT workflows using Python, Spark, and modern orchestration tools.
Improve data quality, validation, monitoring, and observability across the platform.
The company is a Berlin-based, remote-first technology company building advanced market intelligence and software solutions for the automotive industry. It operates in a stable growth phase with an established product and a strong technical team.
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows on AWS.
Modernize legacy data platforms and optimize data pipelines for performance, scalability, and cost efficiency.
Implement data governance, data quality frameworks, and collaborate with stakeholders to enable analytics and reporting.
Tech Holding is a full-service consulting firm that delivers predictable outcomes and high-quality solutions to clients. Our founders and team members have deep industry experience from startups to Fortune 50 companies, guided by principles of expertise, integrity, transparency, and dependability.
Enable efficient data access by creating and maintaining data pipelines.
Collaborate with ML engineers to design and maintain automation for machine learning training, quality assessment, and model release.
Build data infrastructure for analytics, hypothesis testing, and company metrics.
Eneba is building an open, safe, and sustainable marketplace for gamers, supporting close to 20 million active users. We are a growing international team that values data-driven decision making and fosters a healthy data culture.
Design, build, and optimize scalable data platforms supporting analytics, AI/ML, and enterprise reporting.
Develop and maintain complex data pipelines using AWS Glue, Step Functions, and Databricks Workflows.
Collaborate with product, engineering, analytics, and ML teams to transform complex data challenges into reliable solutions.
Jobgether uses AI to match candidates with job openings for faster, fairer reviews. It is a technology platform focused on streamlining the hiring process for both candidates and employers.
Lead impactful customer technical projects by delivering production-grade systems spanning data engineering, AI, and application development.
Guide strategic customers in implementing end-to-end big data and AI projects, including architecture, design, build, and deployment.
Empower customers by providing architecture guidance and ensuring solutions are secure, scalable, and aligned with Databricks best practices.
Databricks is the data and AI company. More than 10,000 organizations worldwide, including Comcast and Condé Nast, rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. The company is headquartered in San Francisco and fosters a diverse, inclusive culture.
Collaborate with Data Science, Product Managers, and Software Engineers to build robust ETL pipelines for user-facing features.
Contribute to architecture decisions, observability tooling, and data quality initiatives to keep the platform robust.
Enforce engineering best practices across the AI/ML org, including code quality, testing, and documentation.
Federato is an AI-native platform for insurance, enabling insurers to provide affordable coverage for climate, cyber, and social inflation risks. It is a small, well-funded company backed by the investors behind Salesforce, Veeva, and Zoom, with a culture focused on first principles, learning, and fun.
Design and deliver end-to-end data solutions for enterprise clients.
Build and maintain modern data lakes, warehouses, and analytical models.
Act as technical point of contact, mentor engineers, and drive quality.
The company is a consulting firm that delivers modern data platforms and analytics solutions for multinational clients. The culture emphasizes collaborative engineering, technical ownership, and work-life balance.
Design and maintain scalable batch and near real-time data pipelines in Databricks, integrating data from various sources.
Build unified customer profiles and support identity resolution, deduplication, enrichment, and Golden Record creation.
Enable CRM and marketing teams to access trusted, activation-ready customer data with minimal latency.
Massive Rocket is a rapidly scaling Braze and Snowflake agency that transforms how digital marketing, product, and engineering teams connect. They have grown quickly in five years and are aiming for $100M in revenue, with a culture of ownership, collaboration, and growth.
Build and maintain batch data pipelines ingesting from Workday and legacy systems into a medallion lakehouse on Azure Databricks and Microsoft Fabric.
Develop transformation logic across Bronze/Silver/Gold layers using Spark, Python, and SQL, and implement data-quality checks.
Work within a federated architecture and Unity Catalog security model, contributing to documentation and code reviews.
CampusWorks is a consulting firm that helps higher education institutions leverage technology and managed services to drive transformation and student success. Founded in 1999, it is a large, virtual company with a culture that values work-life balance and employee appreciation.
Design and build ingestion pipelines from enterprise source systems into the Databricks lakehouse using Delta Lake, owning Bronze-layer ingestion and building Silver-layer pipelines for cleansing and standardization.
Implement and maintain Databricks platform constructs for secure delivery, including catalogs, schemas, service principals, and job orchestration, and build CI/CD pipelines for data platform assets.
Apply data classification and segregation requirements within pipeline design, build data quality controls reflecting business meaning, and partner with teams to ensure reliable, governed data for downstream use.
Shield AI is a venture-backed defense-tech company founded in 2015 with the mission of protecting service members and civilians with intelligent systems, developing products like Hivemind autonomy software and V-BAT and X-BAT aircraft. The company has offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, and its technology actively supports operations worldwide.
Design and implement end-to-end data solutions using Azure Databricks, PySpark, and Azure Data Factory.
Drive automation in data integration and build API-based integrations and real-time ingestion frameworks.
Lead technical design reviews, mentor junior engineers, and partner with business stakeholders.
Alimentiv is a life sciences and healthcare technology company that provides data solutions and analytics. The corporate operations team in Bangalore focuses on technology and innovation, employing a team of engineers and data professionals.
Build, expand, and optimize data infrastructure to create the most accurate dataset of identities and their relationships.
Develop and operate secure, scalable, and reliable data ingestion and ETL/ELT pipelines that meet product requirements.
Design and maintain a data observability framework to ensure data meets strict quality and freshness standards.
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. The company is growing rapidly, has verified hundreds of millions of identities, and is backed by top investors like Craft Ventures and Andreessen Horowitz, with offices across the US and India.
Build, maintain, and optimize scalable data infrastructure for AI/ML features.
Partner with ML Engineers, Data Scientists, and Software Engineers to transform healthcare data into high-quality datasets.
Contribute to data pipelines, improve data quality, and ensure reliable, performant, and well-governed data for AI systems.
Tebra is the only all-in-one EHR+ platform built exclusively for independent healthcare practices. More than 42,000 private practices trust Tebra to streamline operations, increase revenue, and reduce burnout, with a culture that values starting with the customer, keeping it simple, staying entrepreneurial, being better together, and celebrating success.
Design, build, and maintain scalable data pipelines using Python, SQL, Snowflake, Dagster, dbt, and AWS.
Own end-to-end data engineering projects from ingestion through to analytics enablement.
Improve monitoring, alerting, and data quality across key pipelines.
Midnite is a next-generation sports betting and gaming platform built for a new wave of players. Over 400,000 players have joined, and the team operates with high ownership and fast iteration in a scale-up environment.
Design and implement robust, scalable data ingestion and transformation pipelines using Databricks, PySpark, and distributed processing.
Implement Delta Lake principles focusing on CDC and schema evolution, and integrate data quality frameworks within CI/CD pipelines.
Develop and optimize complex SQL and Python scripts, handling diverse data sources and supporting data governance solutions.
Mobile Wave Solutions is a professional services company specializing in software development as a service. With a team of over 120 engineers, we deliver scalable, high-quality software that empowers our global clients to innovate and grow.
Drive migration of legacy Hadoop/Spark/Impala data pipelines to a modern Databricks-centric stack.
Design and build scalable Airflow DAGs and Databricks Jobs for large-scale data pipelines.
Implement robust validation strategies to ensure data parity and quality between legacy and modern systems.
LivePerson is a leader in trusted enterprise conversational AI and digital transformation. Named the #1 Most Innovative AI Company by Fast Company, we power nearly a billion conversational interactions every month for top global brands.